Scenario Forecasting for Global Tourism

This study provides innovative forecasts of the probabilities of certain scenarios of tourism demand. The scenarios of interest are constructed in relation to tourism growth and economic growth. The probability forecasts based on these scenarios provide valuable information for destination policy makers. The time-varying parameter panel vector autoregressive (TVP-PVAR) model is adopted for scenario forecasting. Both the accuracy rate and the Brier score are used to evaluate the forecasting performance. A global set of 25 tourism destinations is empirically examined, and the results confirm that the TVP-PVAR model with a time-varying error covariance matrix is generally a promising tool for forecasting. Our study contributes to tourism forecasting literature in advocating the use of scenario forecasting to facilitate industry decision making in situations wherein forecasts are defined by two or more dimensions simultaneously. In addition, it is the first study to introduce the TVP-PVAR model to tourism demand forecasting

How competitive is Hong Kong against its competitors? An econometric study

This study utilizes almost ideal demand system (AIDS) models to examine Hong Kong's competitiveness as an international tourist destination in comparison with its competitors. The empirical findings of the study shed new light on the destination competitiveness literature and demonstrate that a destination's competitiveness should be examined from a market-specific perspective. The results also suggest that Hong Kong is more competitive than Macau, particularly in terms of its ability to attract Australian and mainland Chinese tourists, while price elasticity calculations suggest Singapore and South Korea are more competitive than Hong Kong

Introduction to the special focus: Tourism forecasting – New trends and issues

Tourism forecasting is one of the longest standing areas in tourism economics research, with over half a century of history already. The development of tourism forecasting research responds and contributes to the industry practice. Accurate demand forecasts are the foundation of tourism-related business decisions on pricing and operation strategies, and for governments on infrastructure investment and tourism policymaking. In recent years, tourism forecasting has received more attention from industry practitioners. First, echoing the increasing numbers of international and domestic tourists, the tourism industry has continuously grown and become more dynamic. As a result, industry practitioners have hoped to understand the market and predict future trends more accurately and comprehensively. Second, in recent years, decision makers have realized the increasing importance of quantitative evidence and have become more likely to rely on or refer to it for their strategy and policy formulations. Finally, the development of big data based on Internet technology has made it possible for the industry to obtain more accurate forecasts. Data on online tourist behaviour can be traced and retrieved. With greater understanding of it, the industry can then use it to forecast future trends.</p

The combination of interval forecasts in tourism

Combination is an effective way to improve tourism forecasting accuracy. However, empirical evidence is limited to point forecasts. Given that interval forecasts can provide more comprehensive information, it is important to consider both point and interval forecasts for decision-making. Using Hong Kong tourism demand as an empirical case, this study is the first to examine if and how the combination can improve interval forecasting accuracy for tourism demand. Winkler scores are employed to measure interval forecasting performance. Empirical results show that combination improves the accuracy of tourism interval forecasting for different forecasting horizons. The findings provide government and industry practitioners with guidelines for producing accurate interval forecasts that benefit their policy-making for a wide array of applications in practice

Impact of domestic tourism on economy under COVID-19: The perspective of tourism satellite accounts

The unprecedented COVID-19 pandemic reversed the ongoing upsurge in the global tourism industry. Yet compared with still-stagnant international tourism, domestic tourism has shown signs of recovery. This study takes Guangdong Province, China as a case for regional domestic tourism and adopts the tourism satellite account (TSA) method to assess domestic tourism's status. A pre- and post-pandemic comparison is conducted to map the impacts of the COVID-19 outbreak on domestic tourism's economic contribution. The TSA results show that the direct contribution of domestic tourism to Guangdong's economy fell from 2.53% to 1.20% across these timeframes. Findings also reveal changes in visitor composition by places of origin and in industries' proportional contributions to tourism

The combination of interval forecasts in tourism

Combination is an effective way to improve tourism forecasting accuracy. However, empirical evidence is limited to point forecasts. Given that interval forecasts can provide more comprehensive information, it is important to consider both point and interval forecasts for decision-making. Using Hong Kong tourism demand as an empirical case, this study is the first to examine if and how the combination can improve interval forecasting accuracy for tourism demand. Winkler scores are employed to measure interval forecasting performance. Empirical results show that combination improves the accuracy of tourism interval forecasting for different forecasting horizons. The findings provide government and industry practitioners with guidelines for producing accurate interval forecasts that benefit their policy-making for a wide array of applications in practice

Measurements of inclusive and differential cross sections for the Higgs boson production and decay to four-leptons in proton-proton collisions at s\sqrt{s} = 13 TeV

Measurements of the inclusive and differential fiducial cross sections for the Higgs boson production in the H $\to$ ZZ $\to$ 4$\ell$ ($\ell$ = e,$\mu$) decay channel are presented. The results are obtained from the analysis of proton-proton collision data recorded by the CMS experiment at the CERN LHC at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$. The measured inclusive fiducial cross section is 2.73$\pm$0.26 fb, in agreement with the standard model expectation of 2.86$\pm$0.1 fb. Differential cross sections are measured as a function of several kinematic observables sensitive to the Higgs boson production and decay to four leptons. A set of double-differential measurements is also performed, yielding a comprehensive characterization of the four leptons final state. Constraints on the Higgs boson trilinear coupling and on the bottom and charm quark coupling modifiers are derived from its transverse momentum distribution. All results are consistent with theoretical predictions from the standard model